Is It Easier to Write a Vulnerability Than to Find One?
Static analysis tools used to be right about as often as a coin flip. Kathleen Goeschel, Principal Product Security Engineer at Red Hat, spent years using machine learning to fix that, and now she's watching large language models change both sides of the fight. How fast vulnerable code gets written, and how fast it gets found.
Goeschel walks through how she trained machine learning models on aggregated scanner alerts, software metrics, and prior CVEs to cut false positives in static analysis, and the surprising finding that code churn alone predicted real vulnerabilities better than most of the signals built for that purpose.
Read the blog post (http://www.buoyant.io/ai-kubernetes-episode/is-it-easier-to-write-a-vulnerability-than-to-find-one?utm_source=spotify&utm_medium=social&utm_campaign=2026.09+ai+k8s+kathleen ) and follow us on LinkedIn (https://www.linkedin.com/company/the-ai-kubernetes-show/ )!
9 Sept 2026
Durable Execution for AI Agents in Kubernetes
If your AI agent restarts and loses everything it was doing, your platform team is stuck retrofitting recovery logic Kubernetes was never built for. Mark Fussell, CEO of Diagrid and creator of the Dapr project, joins the AI Kubernetes Show to explain why that's the real infrastructure problem in the agentic AI era, not the model.
Fussell built the platform running Azure SQL Server at scale during 20 years at Microsoft, then spent the last 9 years building Dapr (Distributed Application Runtime), now a CNCF-graduated project. He and host William Morgan cover durable execution and why he calls it "process reincarnation," why non-determinism and multi-minute latency break assumptions that held for a decade of microservices, and why he tells platform teams to translate what they already know instead of relearning it.
TAKEAWAYS
✓ Why durable execution, or "process reincarnation," matters more once language models are in the call path
✓ How to decide when to keep a workflow deterministic instead of routing it through a model
✓ Why non-determinism, not topology, is the real thing that changed since microservices
✓ How Dapr assigns identity at the process level using the SPIFFE standard, and why that matters for agents
✓ Why a log isn't the same thing as tamper-proof attestation
✓ Why Fussell says about 90% of existing platform engineering skills transfer directly to agentic systems
Read the blog post (http://www.buoyant.io/ai-kubernetes-episode/durable-execution-for-ai-agents-in-kubernetes?utm_source=spontify+apple+music&utm_medium=social&utm_campaign=2026.09+ai+k8s+fussell )!
FIND AND FOLLOW US ON LINKEDIN (https://www.linkedin.com/company/the-ai-kubernetes-show/ )
✦ LinkedIn: https://www.linkedin.com/company/the-ai-kubernetes-show/
26 Aug 2026
Matt Barker (BoltMCP) on SPIFFE, AI Agent Identity, and Kubernetes
AI-generated code is 40% more likely to leak a secret. Matt Barker, co-founder of the company that built cert-manager and later led secure workload access at CyberArk, explains why SPIFFE might finally fix workload identity for AI agents.
Matt and William Morgan cover why SPIFFE replaces long-lived secrets with short-lived, cryptographic workload identities, what Matt is building at BoltMCP to control what an AI agent can see and do once it's trusted, and why CISOs are being told to enable AI adoption "at all costs."
Topics covered:
Why SPIFFE replaces secrets with short-lived workload identities (SVIDs)
Where SPIFFE's job ends and human-delegated authorization begins
Why "context window flooding" breaks MCP integrations at scale
Why Kubernetes stays the default foundation for agentic AI infrastructure
Read the blog post: SPIFFE Identity for AI Agents on Kubernetes (https://www.buoyant.io/ai-kubernetes-episode/spiffe-identity-for-ai-agents-on-kubernetes)
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